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Image time series processing for agriculture monitoring

Herman Eerens, Dominique Haesen, Felix Rembold, Ferdinando Urbano, Carolien Tote, Lieven Bydekerke
2014 Environmental Modelling & Software  
Data from remote sensing image series at high temporal and low spatial resolution can help to assist in this monitoring as they provide key information in near-real time over large areas.  ...  Given strong year-to-year variability, increasing competition for natural resources, and climate change impacts on agriculture, monitoring global crop and natural vegetation conditions is highly relevant  ...  Acknowledgements SPIRITS was developed by VITO for the Joint Research Centre of the European Commission.  ... 
doi:10.1016/j.envsoft.2013.10.021 fatcat:dw7lisfduvblzih2sbdzyxoov4

REVIEW OF MONITORING AND FORECASTING TOOLS OF THE CROP YIELD

Mingxin Huang
2019 Figshare  
A theoretical basis for research was created to solve the problem of creating an information technology for monitoring the yield of agricultural crops based on the analysis of multispectral images obtained  ...  The geoinformation system created on the basis of this technology should monitor and yield the analysis of satellite time series of images to identify quantitative and qualitative indicators of yield,  ...  The articles [10 -12] describe the methods and technologies for processing time series of digital images for decisionmaking in agriculture.  ... 
doi:10.6084/m9.figshare.9788696 fatcat:6ybg4dzetzccddblgtc4654lwq

Agricultural Monitoring in Regional Scale Using Clustering on Satellite Image Time Series [chapter]

Renata Ribeiro do Valle Gonçalves, Jurandir Zullo Junior, Bruno Ferraz do Amaral, Elaine Parros Machado Sousa, Luciana Alvim Santos Romani
2018 Time Series Analysis and Applications  
The remote sensing images are more accessible nowadays and there are proper technologies to receive, distribute, manipulate and process long satellite image time series that can be used to improve traditional  ...  methods for harvest monitoring and forecasting.  ...  Acknowledgements The authors thank FAPESP/AlcScens and CNPq for funding and Cepagri/Unicamp for the database of remote sensing imagery.  ... 
doi:10.5772/intechopen.71148 fatcat:gtx5dhjourh2neplwhh4cqy4ty

Sentinel-2 Based Temporal Detection of Agricultural Land Use Anomalies in Support of Common Agricultural Policy Monitoring

Urška Kanjir, Nataša Đurić, Tatjana Veljanovski
2018 ISPRS International Journal of Geo-Information  
In this paper, we investigate the analysis of a time series approach using Sentinel-2 images and the suitability of the BFAST (Breaks for Additive Season and Trend) Monitor method to detect changes that  ...  The results confirm that the proposed combined approach proves efficient to deal with short time series and yields high accuracy rates in monitoring agricultural parcel greenness.  ...  Acknowledgments: The authors would like to thank Paul Steed and Liza Stančič for language editing and three reviewers for their valuable feedback and comments on the manuscript, which improved it remarkably  ... 
doi:10.3390/ijgi7100405 fatcat:qs6cdxcoqzbfbn322o6o27vd2m

Crop Phenology-Based, Object-Oriented Classification Approach Using SENTINEL-2A and NDVI Time Series: Sunflower Crops in Kırklareli TURKEY

Armağan ALOE KARABULUT, Nihal CEYLAN, Erdem BAHAR, İlker KURŞUN
2021 International Journal of Environment and Geoinformatics  
A time series of spectral signatures of crop phenological periods and normalized difference vegetation index (NDVI) was produced from satellite images for year 2018.  ...  The aim of this study is to develop a methodology for determining sunflower cultivated areas using high resolution time series of the SENTINEL-2A satellite images that represent phenological stages of  ...  Acknowledgements This study was performed within the scope of the "National Product Monitoring and Yield Estimation K., Ustuner, M., Goksel, C., Gazioğlu, C., Kurucu, Y. (2018)  ... 
doi:10.30897/ijegeo.858456 fatcat:jmnpdfigazcdjgwz5ugbztdtgi

A Data Cube of Big Satellite Image Time-Series for Agriculture Monitoring [article]

Thanassis Drivas, Vasileios Sitokonstantinou, Iason Tsardanidis, Alkiviadis Koukos, Charalampos Kontoes, Vassilia Karathanassi
2022 arXiv   pre-print
Time-Series (SITS) analysis via services pertinent to the monitoring of the CAP (e.g., detecting trends and events, monitoring the growth status etc.).  ...  In this work, we present the Agriculture monitoring Data Cube (ADC), which is an automated, modular, end-to-end framework for discovering, pre-processing and indexing optical and Synthetic Aperture Radar  ...  SATELLITE IMAGE TIME-SERIES ANALYSIS Long and dense SITS are essential for agriculture monitoring since crops change dynamically with time.  ... 
arXiv:2205.07752v1 fatcat:mcu6wzpvfjh45mrxl7sqehgusm

Application of nanosatellites PlanetScope data to monitor crop growth

Svitlana Kokhan, Anatoliy Vostokov, K. Jóźwiakowski, T. Ciesielczuk
2020 E3S Web of Conferences  
In this research, an approach to monitor crop growth and development is presented using time series satellite data of high spatial resolution.  ...  The proposed simplified technique, based on PlanetScope NDVI time series, demonstrates the possibilities to monitor temporal changes in crop growth.  ...  Acknowledgements Publication is funded by the Polish National Agency for Academic Exchange under the International Academic Partnerships Programme from the project "Organization of the 9th International  ... 
doi:10.1051/e3sconf/202017102014 fatcat:p6fdpwq3mjejfk7dofabl6jb6q

A Transferable Sentinel-based Agriculture Monitoring Scheme

Vasileios Sitokonstantinou, Ioannis Papoutsis, Charalampos Kontoes
2019 Zenodo  
The methodology uses a parcel-based satellite image (Sentinel-2) time-series approach, under a supervised classification scheme.  ...  monitoring of the agricultural landscape.  ...  Using Sentinel-2 Data Time-Series for the Monitoring of the Common Agricultural Policy. doi: https://doi.org/10.3390/rs10060911 www.beyond-eocenter.eu 38th Annual EARSeL Symposium 9-12 July 2018 Earth  ... 
doi:10.5281/zenodo.2549254 fatcat:frj5a5uup5cazj5kz7cwjytoou

MONITORING THE CROPS PHENOLOGY USING TIME SERIES SENTINEL 2 IMAGES

Iuliana Gabriela Breaban, Alexandra Petronela Stoleriu, Al. I. Cuza" University of Iasi, Faculty of Geography and Geology
2020 Acta Geobalcanica  
The aim of this study was to understand the phenological stages of the crops and to monitor the crops taking into account the time-series images and vegetation indices.  ...  By studying the phenology of the terrestrial surface in accordance with the crop calendar using time series of vegetation indices obtained from Sentinel 2 images, a new way of monitoring the vegetation  ...  Iuliana Gabriela Breaban Alexandra Petronela Stoleriu Monitoring the crops phenology using time series Sentinel 2 images.  ... 
doi:10.18509/agb.2020.10 fatcat:3eav5lmzyfbuhmht75akoqur5q

Fusion Approach for Remotely-Sensed Mapping of Agriculture (FARMA): A Scalable Open Source Method for Land Cover Monitoring Using Data Fusion

Nathan Thomas, Christopher S. R. Neigh, Mark L. Carroll, Jessica L. McCarty, Pete Bunting
2020 Remote Sensing  
Here, we demonstrate the Fusion Approach for Remotely-Sensed Mapping of Agriculture (FARMA), using a suite of open source software capable of efficiently characterizing time-series field-scale statistics  ...  The increasing availability of very-high resolution (VHR; <2 m) imagery has the potential to enable agricultural monitoring at increased resolution and cadence, particularly when used in combination with  ...  Acknowledgments: MAXAR data were provided by NASA's Commercial Archive Data for NASA investigators (cad4nasa.gsfc.nasa.gov) under the National Geospatial-Intelligence Agency's NextView license agreement  ... 
doi:10.3390/rs12203459 fatcat:7vy2tm6pjjg25ovyo33alpqydq

Концептуальна модель геоiнформацiйної системи для сiльського господарства

М. Хуан, Є. Є. Шабала
2019 Науковий вісник Ужгородського університету. Серія: Математика і інформатика  
of time series images obtained by photographing the acreage, in order to evaluate and predict the potential.  ...  Three main tasks of the geoinformation system for agriculture are formulated: calculation of values of time series NDVI indicators based on snapshots, calculation of land quality indicators based on a  ...  Image time series processing for agriculture monitoring. Environmental Modelling and Software, 53, 154-162, https://doi.org/10.1016/j.envsoft.2013.10.021 9. Huang, M. (2019).  ... 
doi:10.24144/2616-7700.2019.2(35).149-155 fatcat:6opbsqlhb5c4bd2yjwujucnsby

Clustering analysis applied to NDVI/NOAA multitemporal images to improve the monitoring process of sugarcane crops

L. A. S. Romani, R. R. V. Goncalves, B. F. Amaral, D. Y. T. Chino, J. Zullo, C. Traina, E. P. M. Sousa, A. J. M. Traina
2011 2011 6th International Workshop on the Analysis of Multi-temporal Remote Sensing Images (Multi-Temp)  
Additionally, we introduce the SatImagExplorer system that was developed to automatically extract time series from a huge volume of remote sensing images as well as provide algorithms of clustering analysis  ...  According to experiments accomplished with spectral images of sugarcane fields, this proposed approach can be satisfactorily used in crop monitoring.  ...  Then, we extracted NDVI values associated to each pixel in all images, generating a time series for each pixel covered by the study area.  ... 
doi:10.1109/multi-temp.2011.6005040 fatcat:j2ujinfxmrbrrpdzvetl6scbu4

DIGITAL IMAGE ANALYSIS TECHNOLOGIES FOR DECISION SUPPORT SYSTEMS IN AGRICULTURAL

Mingxin Huang, Vatskel Vladimir
2019 Figshare  
The paper formulates the research tasks arising from the review of geoinformation technologies and technologies for the analysis of digital images of sown areas.  ...  The paper describes information technologies for efficient management of crop yields and decision-making support in agriculture as a whole.  ...  The work [17] [18] [19] describes methods and technologies for processing time series of digital images for decision-making in agriculture.  ... 
doi:10.6084/m9.figshare.9783227.v1 fatcat:li7wqqguvjbtdekjsj7pn6ii6a

Building a Data Set over 12 Globally Distributed Sites to Support the Development of Agriculture Monitoring Applications with Sentinel-2

Sophie Bontemps, Marcela Arias, Cosmin Cara, Gérard Dedieu, Eric Guzzonato, Olivier Hagolle, Jordi Inglada, Nicolas Matton, David Morin, Ramona Popescu, Thierry Rabaute, Mickael Savinaud (+18 others)
2015 Remote Sensing  
Images were pre-processed to Level 2A and the quality of the resulting time series was assessed.  ...  of open source processing chains for relevant products.  ...  This work has been possible thanks to the SPOT4 (Take 5) time series, which is the main source of the data set presented here.  ... 
doi:10.3390/rs71215815 fatcat:jisj4mm275dotn3s6oipxt3ksy

Discussion on Remote Sensing Monitoring of Agrometeorological Disasters

Litian Wen
2020 Remote Sensing  
Based on this, it comprehensively explores the specific situation of monitoring different disasters by remote sensing monitoring technology in the agricultural production process.</p>  ...  <p>The continuous development of modern society and economy puts forward higher requirements for agricultural production in China.  ...  At the same time, it can also track and monitor for a long time. The destructive power is large, involving a wide range of agricultural disasters.  ... 
doi:10.18282/rs.v9i2.1371 fatcat:hxhzhtvak5dn7b23u74igqqyme
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